62 citations · 186 across the 33 of their papers we have counts for
6 papers · 1 filter
Question's Gambit: The First Move Matters in Agentic Deep Search
Radin Hamidi Rad, Amin Bigdeli, Negar Arabzadeh +4
Deep research agents answer complex questions through iterative loops of searching, reading, and reasoning. Recent work on reasoning-intensive benchmarks such as BrowseComp-Plus sh…
Multi-Agent Transactive Memory
To Eun Kim, Xuhong He, Dishank Jain +3
The decentralized deployment of LLM agents with diverse capabilities across diverse tasks motivates infrastructure for knowledge sharing across heterogeneous agent populations. Jus…
Natural Language Query to Configuration for Retrieval Agents
Melissa Z. Pan, Negar Arabzadeh, Mathew Jacob +3
Modern retrieval agents expose many configuration choices -- LLM, retriever, number of documents, number of hops, and synthesis strategy -- each shaping both answer quality and ser…
IDAT: A Multi-Modal Dataset and Toolkit for Building and Evaluating Interactive Task-Solving Agents
Shrestha Mohanty, Negar Arabzadeh, Andrea Tupini +5
Seamless interaction between AI agents and humans using natural language remains a key goal in AI research. This paper addresses the challenges of developing interactive agents cap…
Transforming Human-Centered AI Collaboration: Redefining Embodied Agents Capabilities through Interactive Grounded Language Instructions
Shrestha Mohanty, Negar Arabzadeh, Julia Kiseleva +6
Human intelligence's adaptability is remarkable, allowing us to adjust to new tasks and multi-modal environments swiftly. This skill is evident from a young age as we acquire new a…
Learning to Solve Voxel Building Embodied Tasks from Pixels and Natural Language Instructions
Alexey Skrynnik, Zoya Volovikova, Marc-Alexandre Côté +9
The adoption of pre-trained language models to generate action plans for embodied agents is a promising research strategy. However, execution of instructions in real or simulated e…